Research Interests
comparative policy studies, legislative studies, political economy, AI and machine learning
Miklós Sebők
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Research Professor (MTA TK PTI)
- Department: Department for Government and Public Policy
- Academic Title: PhD
- Administrative Duties: poltextLAB
- Email: sebok.miklos@tk.hun-ren.hu
- Phone: + 36 1 224 6700 / 5255
- Building: T (Floor, room: 2.22.)
- List of Publications (MTMT)
Selected Publications
2024 The geopolitics of vaccine media representation in Orbán’s Hungary—an AI-supported sentiment analysis (Co-authors: Orsolya Ring, Márk György Kis, Martin Balázs Bánóczy, Ágnes Dinnyés) Journal of Computational Social Science.
2024 Leveraging Open Large Language Models for Multilingual Policy Topic Classification: The Babel Machine Approach (Co-authors: Máté Ákos, Orsolya Ring, Viktor Kovács, Richárd Lehoczki) Social Science Computer Review, 0(0): 1–23.
2024 Staying on the Democratic Script? A Deep Learning Analysis of the Speechmaking of U.S. Presidents (Co-authors: Amnon Cavari, Ákos Máté), Policy Studies Journal. 52(4): 709–729.
2023 Comparative European legislative research in the age of large-scale computational text analysis: A review article (Co-authors: Sven-Oliver Proksch, Christian Rauh, Péter Visnovitz, Gergő Balázs, Jan Schwalbach), International Political Science Review, 0(0): 1–22.
2022 How Orbán won? Neoliberal disenchantment and the grand strategy of financial nationalism to reconstruct capitalism and regain autonomy. Socio-Economic Review
2022 Punctuated Equilibrium and Progressive Friction in Socialist Autocracy, Democracy and Hybrid Regimes (Co-authors: Ágnes M. Balázs, Csaba Molnár), Journal of Public Policy 42 (2): 247–69.
2020 The Multiclass Classification of Newspaper Articles with Machine Learning: The Hybrid Binary Snowball Approach (Co-author: Zoltán Kacsuk), Political Analysis 29 (2): 236–49.